How to unlock the numbers in niche indications by using Multi-Criteria Decision Analysis

If you’re in a highly specialized area, such as MedTech or rare diseases, you’ll be only too familiar with the challenges of working with small sample sizes. Qualitative insights are important but when go/no go decisions are at stake, you may need a more data-driven approach. But, how can you obtain robust market data for decision-making when your target population and treating physicians are limited?

Having worked with leading pharma companies over the years, our team recognizes the issues that small samples present. Since we never want to sacrifice analytical rigor, especially when key milestones in product development are involved, we realized this was a dilemma we wanted to tackle. Always keen to explore (and validate) new research techniques, we’re recommending a creative approach that addresses small HCP samples and delivers big value. Here, I’ll explain how leveraging a little used tool in pharma market research – Multi-Criteria Decision Analysis (MCDA) – can reap a big impact. 

In search of answers

Imagine it’s decision time for further investment in your new niche drug. To move forward, you need to know how HCPs perceive the product and how it would impact their prescribing. What can you do? You could try asking them direct questions about their preferences for particular product characteristics. Except this wouldn’t give you any sense of the value or importance. Or you could ask them to rate different attributes. Except these scores invariably show low discrimination.

Alternatively, you could apply trade-off techniques like conjoint analysis, using product profiles to explore their choices and then analyze the drivers. With a scored measure of utility or value you could then model preference shares for your drug, appropriately weighted and calibrated. Except you don’t have a large enough sample to get a full read on all the product characteristics. Enter MCDA...

MCDA: A creative solution to a pharma insights challenge

MCDA is a flexible method that supports decision-making, while accounting for trade-offs between multiple criteria. It delivers quantitative data, but is widely used in qualitative settings to give insights into the relative value a new therapy may have to decision-makers. Unlike conjoint, MCDA can handle small sample sizes, is easy to set up and uses fixed product profiles that allow each characteristic to be evaluated individually and assigned a weighted score. While not widely used in pharma market research today, it has proven applications in healthcare including risk-benefit assessment, HTA and portfolio analysis decision-making.

SKIM MCDA and pharma market research
Putting MCDA to the test

Combining qualitative research with MCDA sounds promising, but can it deliver comparably robust data to a traditional conjoint exercise? Before recommending it to our clients, we put this question to the test by validating the approach in a small sample of dermatologists evaluating a new oral treatment for a rare skin disease. The validation compared: 1. a quantitative online survey with follow-up in-depth interviews and 2. Two focus groups, plus MCDA exercises.

The objective of this research was to:

  1. Understand HCPs initial reaction to the product

  2. Predict the intended level of adoption

  3. Determine the key drivers of proposed adoption

In terms of these goals, both methods derived very similar insights that led us to the same final conclusion. However, a key advantage of using MCDA was its ability to substantiate and augment the qualitative research. By allowing physicians to consider all attributes simultaneously with equal attention, it enabled a tangible understanding of the interactions between them and a more consistent, unbiased evaluation of the impact of each on decision-making.

A significant revelation from the rating exercise was that uptake of the product could be increased and surpass other products just by improving efficacy alone – a finding that qualitative interviews alone may not have uncovered.

SKIM MCDA and HCP focus groups

Also, physicians stated how they enjoyed providing feedback in a qualitative setting through group conversation. Including this interaction as part of the overall evaluation allows for an authentic environment, mirroring the way in which HCPs confer with, and influence each other, in real life when assessing therapeutic innovations.

When to consider an MCDA approach

MCDA provides comparable output to traditional conjoint, with the added benefit of being qualitative in nature whilst collecting quantitative data. The semi-structured nature of the discussion keeps HCPs focused on the questions in hand and makes the final comparison consistent. However, it will not be an appropriate choice in every case. Depending on your business question, we recommend considering MCDA in the context of innovative product development if you want to understand the impact of new therapies on future prescribing and identify the key drivers when a large-scale quantitative study is unfeasible.

In particular, it allows you to:

  • Add more granularity and data robustness to qualitative research

  • Make a go/no go decision for a new product

  • Assess a universe of prescribers that is too small for strong conjoint analysis

  • Build rigorous data for a broader network of influencers, such as payers and purchasers

 SKIM MCDA small HCP samples big impact

Adapt your insights strategy to today's environment

At SKIM we recognize the marketing challenges you face at the critical stages in the pharmaceutical and MedTech development process. Whether it’s tackling value-based pricing or unraveling complicated physician/patient/payer decision journeys, it’s critical you adapt your research strategy to thrive in today’s competitive landscape.

From traditional forecasting and market mapping, to post-launch growth strategies, we have a 40-year proven track record of helping leading companies achieve more from their research with large and small HCP samples alike. 

Curious to know if MCDA may be the right approach for you? Contact us today to learn more.

 

Daisy Lau

Written by Daisy Lau

Daisy is a Senior Research Manager based in Rotterdam. Her expertise lies in coordinating large multi-country projects in the healthcare arena, conducting both quantitative and qualitative research. Having worked with pharmaceutical, medical device and other B2B companies, she holds deep knowledge of the analytical techniques and software required for methodology design, execution and interpretation. Daisy holds a Biology degree from Simon Fraser University, B.C., Canada.

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